[B! numpy] digimedaloterã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯

digimedaloter id:digimedaloter

numpyã«é–¢ã™ã‚‹digimedaloterã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (18)

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ç§è¨³ã€Œæš«å®šçš„ NumPy ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã€ - naoya_t@hatenablog
# åŽŸæ–‡ï¼šhttp://www.scipy.org/Tentative_NumPy_Tutorial ã“ã®ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã‚’èªã‚€å‰ã«ã€Pythonã«ã¤ã„ã¦ã¡ã‚‡ã£ã¨ã¯çŸ¥ã£ã¦ã„ã‚‹ã¹ãã ã€‚è¨˜æ†¶ã‚’ãƒªãƒ•ãƒ¬ãƒƒã‚·ãƒ¥ã—ãŸã„ã¨æ€ã†ãªã‚‰ã€Pythonãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã‚’è¦‹ã¦ãã‚‹ãŒã„ã„ã€‚ ã“ã®ãƒãƒ¥ãƒ¼ãƒˆãƒªã‚¢ãƒ«ã«å‡ºã¦ãã‚‹ä¾‹ã‚’è©¦ã—ãŸã„ãªã‚‰ã€ã‚ãªãŸã®PCã«å°‘ãªãã¨ã‚‚ Python NumPy ã¯ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã•ã‚Œã¦ã„ã‚‹ã¹ãã§ã€ä»–ã«å…¥ã£ã¦ã‚‹ã¨ä¾¿åˆ©ãªã®ã¯ï¼š ipython ã¯æ‹¡å¼µã•ã‚ŒãŸã‚¤ãƒ³ã‚¿ãƒ©ã‚¯ãƒ†ã‚£ãƒ–ãªPythonã‚·ã‚§ãƒ«ã§ã€NumPyã®æ©Ÿèƒ½ã‚’æŽ¢æ¤œã™ã‚‹ã®ã«ã¨ã¦ã‚‚ä¾¿åˆ© matplotlib ãŒã‚ã‚‹ã¨å›³è¡¨ã®æç”»ãŒå¯èƒ½ã«ãªã‚‹ SciPy ã¯NumPyã®ä¸Šã§å‹•ãç§‘å¦è¨ˆç®—ãƒ«ãƒ¼ãƒãƒ³ã‚’æ²¢å±±ç”¨æ„ã—ã¦ãã‚Œã‚‹ åŸºç¤Ž NumPy ã®ä¸»è¦ãªã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã¯ã€åŒã˜åž‹ï¼ˆæ™®é€šã¯æ•°ï¼‰ã®è¦ç´ ã®ã¿ã‹ã‚‰æˆã‚Šã€æ£ã®æ•´æ•°ã®ã‚¿ãƒ—ãƒ«ã§æ·»å—ä»˜ã‘ã•ã‚ŒãŸã€å‡è³ªãªãƒ†ãƒ¼ãƒ–ãƒ«ï¼ˆã¨ã„ã†ã‹å¤šæ¬¡å…ƒ
digimedaloter 2014/06/02
python

numpy
ãƒªãƒ³ã‚¯
Atsushi TATSUMA Web Page Â» OpenBLAS ã‚’ä½¿ã£ãŸ Numpy/Scipy ã®ãƒ“ãƒ«ãƒ‰
ã¯ã˜ã‚ã« ã“ã‚Œã¾ã§ BLAS ã«ã¯ã€é«˜é€Ÿãª GotoBLAS ã‚’ä½¿ã£ã¦ãã¾ã—ãŸãŒã€ é–‹ç™ºãŒçµ‚äº†ã—ã¦ã„ã‚‹ã“ã¨ã‹ã‚‰ã€ç§»è¡Œå…ˆã‚’æ¤œè¨Žã—ã¦ã„ã¾ã—ãŸã€‚ GotoBLAS ã®å¾Œç¶™ã§ã‚ã‚Šã€é–‹ç™ºãŒç¶šã„ã¦ã„ã‚‹ã“ã¨ã‹ã‚‰ã€OpenBLAS ã‚’ä½¿ã†ã“ã¨ã«ã—ã¾ã—ãŸã€‚ ç ”ç©¶å®¤ã§ã¯ Debian GNU/Linux ã‚’ä½¿ç”¨ã—ã¦ãŠã‚Šã€ä½œæ¥å½“æ™‚ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã¯ squeeze ã§ã™ã€‚ æº–å‚™ å¿…è¦ãªãƒ©ã‚¤ãƒ–ãƒ©ãƒªãªã©ã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«/ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã—ã¾ã™ã€‚ ã¾ãšã€ä»Šå›žã€ç‹¬è‡ªã«ãƒ“ãƒ«ãƒ‰ã—ãªã„ãƒ©ã‚¤ãƒ–ãƒ©ãƒªãªã©ã‚’ aptitude ã§ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¾ã™ã€‚ libatlas-base-dev ãŒã€å¾ŒåŠã§é‡è¦ã¨ãªã‚Šã¾ã™ã€‚ $ sudo aptitude install gfortran git swig $ sudo aptitude install python python-numpy python-scipy python-nose
digimedaloter 2014/03/30
numpy

blas
ãƒªãƒ³ã‚¯
Numpy.hpp - .npyãƒ•ã‚¡ã‚¤ãƒ«ã‚’æ‰‹è»½ã«æ‰±ã†ãŸã‚ã®ãƒ˜ãƒƒãƒ€ãƒ©ã‚¤ãƒ–ãƒ©ãƒª
Introduction ã”å˜çŸ¥ã®é€šã‚Šï¼ŒC++ã¯ç”»åƒå‡¦ç†ãªã©ã®å¤§è¦æ¨¡è¨ˆç®—ã«é©ã—ãŸè¨€èªžã§ã‚ã‚Šï¼ŒPythonã¯ã“ã‚Œã‚‰ã®çµæžœã‚’ç°¡å˜ã«scipyã‚„matplotlibã‚’ä½¿ã£ã¦å¯è¦–åŒ–ã§ãã¾ã™ï¼Žãã®ãŸã‚ï¼Œå¤šãã®ç ”ç©¶è€…ã¯ã‚³ã‚¢ã®è¨ˆç®—ã‚’C++ã§è¡Œã†ä¸€æ–¹ã§ï¼Œãƒ‡ãƒ¼ã‚¿æ•´ç†ã‚„å®Ÿé¨“çµæžœã®å¯è¦–åŒ–ã«ã¯Pythonã‚’ç”¨ã„ã‚‹ã‚¢ãƒ—ãƒãƒ¼ãƒãŒä¸€èˆ¬çš„ã§ã—ãŸï¼Ž ãã®éš›ã«é‡è¦ã¨ãªã£ã¦ãã‚‹ã®ã¯ï¼ŒNumpyæ¨™æº–ã®ãƒ•ã‚¡ã‚¤ãƒ«å½¢å¼ã§ã‚ã‚‹.npyãƒ•ã‚¡ã‚¤ãƒ«ã‚’èªã¿æ›¸ãã™ã‚‹ãŸã‚ã®ï¼ŒC++ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã®å˜åœ¨ã§ã™ï¼Žã“ã‚Œã¾ã§ã«ã‚‚libnpyãªã©ã«ä»£è¡¨ã•ã‚Œã‚‹ã„ãã¤ã‹ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒªãŒå˜åœ¨ã—ã¦ã„ã¾ã—ãŸãŒï¼Œäºˆã‚ã‚³ãƒ³ãƒ‘ã‚¤ãƒ«ã™ã‚‹å¿…è¦ãŒã‚ã‚‹ãŸã‚æ°—è»½ã«ä½¿ãˆãªã„ï¼Œã¾ãŸMSVCãªã©ã®ç’°å¢ƒã§ä½¿ç”¨ã§ããªã„ãªã©ã®ã„ãã¤ã‹ã®æ¬ ç‚¹ãŒã‚ã‚Šã¾ã—ãŸï¼Ž Numpy.hppã¯ã“ã‚Œã‚‰ã®å•é¡Œã‚’è§£æ±ºã™ã‚‹ãŸã‚ã«ä½œã‚‰ã‚ŒãŸãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã™ï¼ŽNumpy.hppã®ç‰¹å¾´ã¯æ¬¡ã®2ã¤ã§ã™ï¼Ž Header-only: Numpy
digimedaloter 2014/03/05
numpy
ãƒªãƒ³ã‚¯
NumPyã®arrayã¨PILã®å¤‰æ› - white wheelsã®ãƒ¡ãƒ¢
Python Imaging Libraryã®Imageã‚¯ãƒ©ã‚¹ã®ãƒ‡ãƒ¼ã‚¿ã‚’Numpyã®arrayã¨ã—ã¦æ‰±ã†ãŸã‚ã®æ–¹æ³•ã«ã¤ã„ã¦ã€‚ Numpyã®é–¢æ•°ã‚’ä½¿ã£ã¦ç›´æŽ¥pixelå€¤ã‚’æ›¸ãæ›ãˆã‚‹ã“ã¨ãŒç›®æ¨™ã§ã™ã€‚ ã¾ãšã¯ä¸¡æ–¹ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã‚’ã‚¤ãƒ³ãƒãƒ¼ãƒˆã—ã¦ãŠãã¾ã™ã€‚ import numpy import Image PILã‹ã‚‰Numpyã®arrayã¸ã®å¤‰æ› numpyã§ç”¨æ„ã•ã‚Œã¦ã„ã‚‹asarrayé–¢æ•°ã‚’ä½¿ã†ã¨ã€PILã®Imageã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã‚’é…åˆ—ã«å¤‰æ›ã™ã‚‹ã“ã¨ãŒã§ãã¾ã™ã€‚ imgArray = numpy.asarray(pilImg) ã•ã‚‰ã«é…åˆ—ã®å€¤ã‚’æ›¸ãå¤‰ãˆã‚‰ã‚Œã‚‹ã‚ˆã†ã«ã™ã‚‹ãŸã‚ã«ã¯ã€writeableãƒ•ãƒ©ã‚°ã‚’Trueã«ã™ã‚‹å¿…è¦ãŒã‚ã‚‹ã‚ˆã†ã§ã™ã€‚ imgArray.flags.writeable = True Numpyã®arrayã‹ã‚‰PILã¸ã®å¤‰æ› PILã®fromarrayãƒ¡ã‚½ãƒƒãƒ‰ã«ã‚ˆã£ã¦ã€é…åˆ—ã®å„å€¤ã‚’1
digimedaloter 2014/02/04
python

numpy
ãƒªãƒ³ã‚¯
Scipy Lecture Notes â€” Scipy lecture notes
One document to learn numerics, science, and data with PythonÂ¶ Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with increasing level of expertise, from beginner to expert.
digimedaloter 2013/10/07
python

scipy

numpy
ãƒªãƒ³ã‚¯
NumPy, SciPyã‚’ã¡ã‚ƒã‚“ã¨ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã™ã‚‹ï¼ˆCentOS+Python2.7+easy_installï¼‰ - Kesinã®çŸ¥è¦‹ç½®ãå ´
ç ”ç©¶å®¤ã«æ–°ã—ãRedHatã®è¨ˆç®—æ©ŸãŒæ¥ã‚‹ãã†ãªã®ã§ã€è‡ªåˆ†ã®MacBookã«VirtualBoxã‚’ä½¿ç”¨ã—ã¦CentOSã‚’å…¥ã‚Œã¦è‡ªåˆ†ã®ç’°å¢ƒã¥ãã‚Šï¼†æ¥å¹´å…¥ã£ã¦æ¥ã‚‹å¾Œè¼©ã«Pythonã‚’å¸ƒæ•™ã™ã‚‹ãŸã‚ã®ç·´ç¿’ãƒ¡ãƒ¢ã€‚ ç›®æ¨™ï¼šã‚·ã‚¹ãƒ†ãƒ ã¨ã¯åˆ¥ã®Pythonã‚’ã‚½ãƒ¼ã‚¹ã‹ã‚‰ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã€‚yumã§ATLASã€easy_installã§numpyã¨scipyã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¦ã¡ã‚ƒã‚“ã¨ATLASã‚’ä½¿ç”¨ã™ã‚‹numpy, scipyç’°å¢ƒã‚’æ§‹ç¯‰ã™ã‚‹ 1. NumPy, SciPy RedHat, CentOSã ã¨yumã§ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã§ãã‚‹numy, scipyãŒPython2.6ã¨å¤ãã€ã‚·ã‚¹ãƒ†ãƒ ã§ä½¿ã£ã¦ã‚‹ã‚‚ã®ã‚’æ±šã•ãªã„æ–¹ãŒã„ã„ã¨æ€ã†ã®ã§è‡ªåˆ†ã®ãƒ¦ãƒ¼ã‚¶ãƒãƒ¼ã‚«ãƒ«ã«Python2.7ã‚’å…¥ã‚Œã¦ã€å®‰å®šç‰ˆã®numpyã¨scipyï¼ˆåŸ·ç†å½“æ™‚ã¯1.6.1ã¨0.10.0ï¼‰ã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã—ã¾ã™ã€‚ numpyã¨scipyã¯è¡Œåˆ—ã‚’é«˜é€Ÿã«è¨ˆç®—ã—ã¦ãã‚Œã‚‹ãƒ¢
digimedaloter 2013/08/07
python

numpy

scipy
ãƒªãƒ³ã‚¯
ç¬¬2å›ž Tokyo.SciPy ã§ã€Œæ•°å¼ã‚’ numpy ã«è½ã¨ã—ã“ã‚€ã‚³ãƒ„ã€ã‚’ç™ºè¡¨ã—ã¦ãã¾ã—ãŸ - æœ¨æ›œä¸è¶³
10/15 ã« IBM ã•ã‚“ã®æ¸‹è°·ã‚ªãƒ•ã‚£ã‚¹ã«ã¦é–‹å‚¬ã•ã‚ŒãŸ ç¬¬2å›ž Tokyo.SciPy ã«ã®ã“ã®ã“å‚åŠ ã—ã¦ãã¾ã—ãŸã€‚ä¸»å‚¬ã® @sla ã•ã‚“ã¯ã˜ã‚ã€å‚åŠ è€…ãƒ»ç™ºè¡¨è€…å„ä½ãŠã¤ã‹ã‚Œã•ã¾ã§ã—ãŸï¼†ã‚ã‚ŠãŒã¨ã†ã”ã–ã„ã¾ã—ãŸã€‚ ã›ã£ã‹ãè¡Œããªã‚‰ãªã‚“ã‹ç™ºè¡¨ã—ãŸã„ã‚ˆãã€ã¨ã„ã†ã“ã¨ã§ã€Œæ•°å¼ã‚’ numpy ã«è½ã¨ã—ã“ã‚€ã‚³ãƒ„ ã€œæ©Ÿæ¢°å¦ç¿’ã‚’é¡Œæã«ã€œã€ãªã‚“ã¦ã‚¿ã‚¤ãƒˆãƒ«ã§ã€æ•°å¼(ã‚ã‚‹ã„ã¯æ•°å¼å…¥ã‚Šã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ )ã‚’å®Ÿè£…ã™ã‚‹ã¨ãã«ã€ã©ã†ã„ã†ç‚¹ã«æ³¨ç›®ã™ã‚Œã°æ˜“ã—ãã‚³ãƒ¼ãƒ‰ã‚’æ›¸ã‘ã‚‹ã‹ã€ã«ã¤ã„ã¦ã¡ã‚‰ã¡ã‚‰èªžã£ã¦ã¿ãŸã€‚ ã“ã¡ã‚‰ãŒãã®è³‡æ–™ã€‚ æ•°å¼ã‚’numpyã«è½ã¨ã—ã“ã‚€ã‚³ãƒ„ View more presentations from Shuyo Nakatani ä¾‹ãˆã°ã€æ©Ÿæ¢°å¦ç¿’ã®(å¤šã‚¯ãƒ©ã‚¹)ãƒã‚¸ã‚¹ãƒ†ã‚£ãƒƒã‚¯å›žå¸°ã¨ã„ã†æŠ€è¡“ã§ã¯ã€æ¬¡ã®ã‚ˆã†ãªæ•°å¼ãŒç™»å ´ã™ã‚‹ã€‚ (PRML (4.109) å¼) ã“ã‚Œã‚’ä¸€ç›®è¦‹ã¦ã™ã‚‰ã™ã‚‰ã¨ã‚³ãƒ¼ãƒ‰ãŒæ›¸ã‘ã‚‹ãªã‚‰è‹¦åŠ´ã¯ãªã„ãŒã€æ…£
digimedaloter 2013/01/07
numpy

python
ãƒªãƒ³ã‚¯
numpy.linalg.invã¨numpy.linalg.solveã‚’ç”¨ã„ãŸé€†è¡Œåˆ—è¨ˆç®— - ã‚·ãƒªã‚³ãƒ³ã®è°·ã®ã‚¾ãƒ³ãƒ“
(Tokyo.SciPyã«æ¯Žåº¦ãŠé‚ªé”ã•ã›ã¦é ‚ã„ã¦ã„ã‚‹ã®ã«ã‚‚é–¢ã‚ã‚‰ãšä»Šã¾ã§å…¨ãNumPyã¨ã‹SciPyã¨ã‹ä½¿ã£ã¦ã„ãªã‹ã£ãŸã®ã ã‘ã‚Œã©) æœ€è¿‘ã‚ˆã†ã‚„ãNumPyã‚„SciPyã‚’(ã»ã‚“ã®)å°‘ã—ãšã¤ä½¿ã†ã‚ˆã†ã«ãªã£ã¦ããŸï¼Žæ©Ÿæ¢°å¦ç¿’é–¢é€£ã«é™ã‚‰ãšå¿…ãšã¨è¨€ã£ã¦ã„ã„ã»ã©ãŠä¸–è©±ã«ãªã‚‹é€†è¡Œåˆ—è¨ˆç®—ï¼Ž ãã†ã„ãˆã°é€†è¡Œåˆ—ã¨ä½•ã‹ã®ç©ã‚’å–ã‚‹å ´åˆï¼Œnumpy.linalg.inv()ã˜ã‚ƒãªãã¦numpy.linalg.solve()ã®æ–¹ãŒé€Ÿã„ã‚ˆï¼Œã¨ã„ã†ã“ã¨ã‚’ã©ã“ã‹ã§èžã„ã¦ã„ãŸæ°—ãŒã™ã‚‹ã®ã§ã€Œå˜ä½è¡Œåˆ—ã¨ã®ç©ã‚’å–ã‚Œã°é€†è¡Œåˆ—å˜ä½“ã®è¨ˆç®—ã‚‚é€Ÿããªã‚‹ã‚“ã˜ã‚ƒã?ã€ã¨ã„ã†ã“ã¨ã‚’ãŠæ€ã„ã¤ã„ã¦é€Ÿåº¦å·®ã‚’æ¯”è¼ƒã—ã¦ã¿ãŸï¼Ž ã¨ã„ã†ã‚ã‘ã§ä»¥ä¸‹ã®4ã¤ã®ã‚±ãƒ¼ã‚¹ã®é€Ÿåº¦ã‚’æ¯”è¼ƒ Aã®é€†è¡Œåˆ—ã‚’è¨ˆç®— (numpy.linalg.inv) Aã®é€†è¡Œåˆ—ã‚’è¨ˆç®— (numpy.linalg.solve) Aã®é€†è¡Œåˆ—ã‚’è¨ˆç®— (numpy.linalg.inv) ã—ï¼Œbã®ç©ã‚’è¨ˆç®—
digimedaloter 2013/01/07
python

numpy
ãƒªãƒ³ã‚¯
SciPy Cookbook â€” SciPy Cookbook documentation
SciPy CookbookÂ¶ This is the â€œSciPy Cookbookâ€ â€” a collection of various user-contributed recipes, which once lived under wiki.scipy.org. If you have a nice notebook youâ€™d like to add here, or youâ€™d like to make some other edits, please see the SciPy-CookBook repository.
digimedaloter 2012/11/25
numpy

scipy

python
ãƒªãƒ³ã‚¯
æ•°å¼ã‚’numpyã«è½ã¨ã—ã“ã‚€ã‚³ãƒ„
Tokyo.SciPy #2 ã«ã¦ç™ºè¡¨ã—ãŸã€æ•°å¼(ã‚ã‚‹ã„ã¯æ•°å¼å…¥ã‚Šã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ )ã‹ã‚‰å®Ÿè£…ã«è½ã¨ã™å ´åˆã€ä½•ã«æ°—ã‚’ã¤ã‘ã‚‹ã®ã‹ã€ã©ã†è€ƒãˆã‚Œã°ã„ã„ã®ã‹ã€ã¨ã„ã†ãŠè©±ã€‚ å¯¾è±¡ã¯ã€ã©ã†ã‚„ã£ã¦æ•°å¼ã‚’ãƒ—ãƒã‚°ãƒ©ãƒ ã™ã‚Œã°ã„ã„ã‹ã‚ˆãã‚ã‹ã‚‰ãªã„äººã€ã¡ã‚‡ã£ã¨ã‚„ã‚„ã“ã—ã„æ•°å¼ã«ãªã‚‹ã¨å››è‹¦å…«è‹¦ã—ã¦ã—ã¾ã„ã€ã‚³ãƒ¼ãƒ‰ã«è½ã¨ã™ã®ã«ã™ã”ãæ™‚é–“ãŒã‹ã‹ã£ã¦ã—ã¾ã†äººã€ãªã©ã€‚ ã“ã“ã§ã¯å®Ÿè¡Œé€Ÿåº¦ã«ã¤ã„ã¦ã¯ã²ã¨ã¾ãšãŠã„ã¨ã„ã¦ã€ç°¡æ½”ã§é–“é•ã„ã«ãã„ã€ã¡ã‚ƒã‚“ã¨å‹•ãã‚³ãƒ¼ãƒ‰ã‚’æ›¸ãã“ã¨ã‚’ç›®æ¨™ã«ã—ã¦ã„ã¾ã™ã€‚ Read less
digimedaloter 2012/10/03
python

ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°

numpy
ãƒªãƒ³ã‚¯
python/numpy - æ©Ÿæ¢°å¦ç¿’ã®ã€Œæœ±é·ºã®æœWikiã€
ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸â€ pip ã‚„ easy_install ã«ã‚ˆã‚‹ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã®å‰ã«å¤šãã®å¤–éƒ¨ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã‚„fortranã‚³ãƒ³ãƒ‘ã‚¤ãƒ©ãªã©ãŒå¿…è¦ã«ãªã‚‹ã®ã§ï¼Œnumpyç‰ã®ç§‘å¦æŠ€è¡“è¨ˆç®—ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚’ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã™ã‚‹ã«ã¯ä»¥ä¸‹ã®ã‚ˆã†ãªãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚’ä¸€èˆ¬ã«ã¯åˆ©ç”¨ã™ã‚‹ï¼š å•†ç”¨ï¼ˆã‚µãƒãƒ¼ãƒˆãªã—ãªã‚‰ç„¡æ–™ã§ã‚‚åˆ©ç”¨ã§ãã‚‹ï¼‰ Anacondaï¼šç„¡æ–™ç‰ˆã§ã‚‚Intel MKLãŒä½¿ãˆã‚‹ Enthought Canopy ãƒ•ãƒªãƒ¼ Unofficial Windows Binaries for Python Extension Packages (å€‹äººãƒ™ãƒ¼ã‚¹ã®ç®¡ç†ã§éžå…¬å¼ç‰ˆ) â†‘ ãã®ä»–â€ pyvideo.orgï¼šPyCon, SciPy, PyData ãªã©ã®è¬›æ¼”ãƒ“ãƒ‡ã‚ªãƒªãƒ³ã‚¯é›† 100 numpy exercisesï¼šç·´ç¿’å•é¡Œ Pythonidaeï¼šPythoné–¢é€£ã®ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã®ãƒªãƒ³ã‚¯é›† SciPy Centralï¼šSciPy é–¢é€£ã‚³
digimedaloter 2012/10/03
numpy

python

ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°
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NumPy â€” NumPy
NumPy is the fundamental package for scientific computing with Python. It contains among other things: a powerful N-dimensional array object sophisticated (broadcasting) functions tools for integrating C/C++ and Fortran code useful linear algebra, Fourier transf orm, and random number capabilities Besides its obvious scientific uses, NumPy can also be used as an efficient multi-dimensional containe
digimedaloter 2012/09/05
numpy

ãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚°

python
ãƒªãƒ³ã‚¯
é«˜é€Ÿæ•°å€¤è¨ˆç®—ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã€ŒNumpyã€è¦šæ›¸ã - Pashangoâ€™s Blog
Pythonã§ä¸€ç•ªæœ‰åã§æ™®åŠã—ã¦ã„ã‚‹ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¨è¨€ã£ã¦ã‚‚éŽè¨€ã§ã¯ãªã„ã€ŒNumpyã€ã®è¦šæ›¸ãã§ã™ã€‚ã‹ãªã‚Šå¤šæ©Ÿèƒ½ãªæ•°å€¤è¨ˆç®—ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã§ã€å†…éƒ¨ã¯Cè¨€èªžã§è¨˜è¿°ã•ã‚Œã¦ã„ã‚‹ãŸã‚è¶…é«˜é€Ÿã«å‹•ä½œã—ã¾ã™ã€‚ ãƒ™ã‚¯ãƒˆãƒ« ãƒ™ã‚¯ãƒˆãƒ«ã®é•·ã•ï¼†æ£è¦åŒ– import numpy a = numpy.array([[2,2]]) #ãƒ™ã‚¯ãƒˆãƒ«ã®é•·ã• length = numpy.linalg.norm(a) #length=>2.8284271247461903 #ãƒ™ã‚¯ãƒˆãƒ«ã®æ£è¦åŒ– a / numpy.linalg.norm(a) #=>array([[ 0.70710678, 0.70710678]]) å†…ç©ï¼†å¤–ç© import numpy v1 = numpy.array((1,0,0)) v2 = numpy.array((0,1,0)) #å†…ç© numpy.dot(v1,v2) #=> 0 #å¤–ç© numpy.cros
digimedaloter 2012/07/24
numpy

Python
ãƒªãƒ³ã‚¯
matplotlibã§3Dã‚°ãƒ©ãƒ•ã‚’æç”»ã™ã‚‹ - white wheelsã®ãƒ¡ãƒ¢
æº–å‚™ ãƒ‡ãƒ¼ã‚¿å‡¦ç†ç”¨ã«numpyã€ãƒ—ãƒãƒƒãƒˆç”¨ã«pyplotã€3æ¬¡å…ƒãªã®ã§mpl_toolkits.mplot3dã‚’ã‚¤ãƒ³ãƒãƒ¼ãƒˆã—ã¾ã™ã€‚ from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np æç”»ã™ã‚‹ãƒ‡ãƒ¼ã‚¿ã®ä½œæˆ 3æ¬¡å…ƒã§æç”»ã™ã‚‹ã«ã¯ãƒ¡ãƒƒã‚·ãƒ¥(2æ¬¡å…ƒã®ç¶²ç›®)ã‚’ä½œæˆã™ã‚‹ãŸã‚ã«2æ¬¡å…ƒã®é…åˆ—ã‚’ç”¨æ„ã™ã‚‹å¿…è¦ãŒã‚ã‚Šã¾ã™ã€‚ ã¾ãšarangeãƒ¡ã‚½ãƒƒãƒ‰ã§x,yãã‚Œãžã‚Œã‚’1æ¬¡å…ƒé ˜åŸŸã§åˆ†å‰²ã—ã¾ã™ã€‚ x = np.arange(-3, 3, 0.25) y = np.arange(-3, 3, 0.25) 2æ¬¡å…ƒãƒ¡ãƒƒã‚·ãƒ¥ã‚’ä½œæˆã™ã‚‹ã«ã¯meshgridãƒ¡ã‚½ãƒƒãƒ‰ã‚’åˆ©ç”¨ã—ã¾ã™ã€‚ã“ã®é–¢æ•°ã®æˆ»ã‚Šå€¤ã¯X,Yã«å¯¾å¿œã™ã‚‹è¡Œåˆ—ã§ã€Xã¯è¡Œã«xã®é…åˆ—ã‚’ã€Yã¯åˆ—ã«yã®é…åˆ—ã‚’å…¥ã‚ŒãŸã‚‚ã®ã«ãªã£ã¦ã„ã¾ã™ã€‚ X, Y =
digimedaloter 2012/07/22
python

matplotlib

numpy
ãƒªãƒ³ã‚¯
pythonã§å¤šæ¬¡å…ƒé…åˆ—ã‚’æ‰±ã† - ãŸã“ç„¼ãé£Ÿã¹ãŸ.net
pythonã§é…åˆ—ã‚’æ‰±ã†ãƒ©ã‚¤ãƒ–ãƒ©ãƒªã¨ã—ã¦æœ‰åãªã®ã¯numpyã¨ã„ã†ã‚‚ã®ã§ã™ã€‚ Python ã¯ã‚¤ãƒ³ã‚¿ãƒ—ãƒªã‚¿è¨€èªžã§ã‚ã‚Šã€æ•°å¦ã®ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã¯Cè¨€èªžãªã©ã®ã‚³ãƒ³ãƒ‘ã‚¤ãƒ«è¨€èªžã‚„Javaãªã©ã¨æ¯”ã¹ã¦ä½Žé€Ÿã«å‹•ä½œã™ã‚‹å ´åˆãŒå¤šã„ã€‚NumPy ã¯ã“ã†ã—ãŸå•é¡Œã‚’ã€å¤šæ¬¡å…ƒé…åˆ—ã¨ã€é…åˆ—ã‚’æ“ä½œã™ã‚‹å¤šæ•°ã®é–¢æ•°ã‚„æ¼”ç®—åã‚’æä¾›ã™ã‚‹ã“ã¨ã§ã“ã®å•é¡Œã‚’è§£ã“ã†ã¨ã—ã¦ã„ã‚‹ã€‚ã“ã‚Œã«ã‚ˆã‚Šã€é…åˆ—ã‚„è¡Œåˆ—ã®æ“ä½œã¨ã—ã¦è¨˜è¿°ã§ãã‚‹ã‚¢ãƒ«ã‚´ãƒªã‚ºãƒ ã¯ã€ç‰ä¾¡ãª C ã®ã‚³ãƒ¼ãƒ‰ã¨ã»ã¼åŒç‰ã®é€Ÿåº¦ã§å‹•ä½œã™ã‚‹ã€‚ NumPy - Wikipedia ã¨ã‚ã‚‹ã‚ˆã†ã«ã€éžå¸¸ã«é«˜é€Ÿã«ã‹ã¤ç°¡å˜ã«è¡Œåˆ—è¨ˆç®—ã‚’è¡Œãªã†ã“ã¨ãŒã§ãã¾ã™ã€‚ matplotlibã¯ã€numpyã®è¡Œåˆ—ã‚’å‡¦ç†ã—ã¦ã‚°ãƒ©ãƒ•ã®ä½œæˆã‚’ã—ã¦ã„ã¾ã™ã€‚ ã¾ãŸã€ãƒ‡ãƒ¼ã‚¿å‡¦ç†ã«ã‚‚æ´»èºã—ã¦ãã‚Œã‚‹ã“ã¨ã§ã—ã‚‡ã†ã€‚ ã¨ã„ã†ã‚ã‘ã§ã€è‡ªåˆ†ãŒã‚ˆãä½¿ã†é–¢æ•°ç‰ã‚’ã¾ã¨ã‚ã¦ãŠãã¾ã™ã€‚ å‚è€ƒè³‡æ–™ å‚è€ƒã«ãªã‚‹ã€å‚è€ƒã«ã—ãŸWebã‚µã‚¤ãƒˆã®ãƒªã‚¹ãƒˆã‚’æŒ™ã’ã¦ãŠãã¾ã™
digimedaloter 2012/07/22
numpy

python
ãƒªãƒ³ã‚¯
Routines and objects by topic â€” NumPy v2.0 Manual
Routines and objects by topic# In this chapter routine docstrings are presented, grouped by functionality. Many docstrings contain example code, which demonstrates basic usage of the routine. The examples assume that NumPy is imported with: A convenient way to execute examples is the %doctest_mode mode of IPython, which allows for pasting of multi-line examples and preserves indentation.
digimedaloter 2012/07/10
numpy

python
ãƒªãƒ³ã‚¯
Introduction to NumPy & SciPy
2. Contents NumPy & Scipy ã®æ©Ÿèƒ½ç´¹ä»‹ â†’ ndarrayã‚¯ãƒ©ã‚¹ã®æ“ä½œã‚’ä¸å¿ƒã«èª¬æ˜Ž NumPy & SciPy ã‚’ä½¿ã£ãŸãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚° â†’ ç·šå½¢å›žå¸°ã€ ä¸»æˆåˆ†åˆ†æž, K-Means â†’ Pythonã®ç‰¹å¾´ã§ã‚ã‚‹OOPã‚‚å–ã‚Šå…¥ã‚Œã‚‹ ndarrayã®viewã¨å‚ç…§æ¸¡ã— 3. Contents NumPy & Scipy ã®æ©Ÿèƒ½ç´¹ä»‹ â†’ ndarrayã‚¯ãƒ©ã‚¹ã®æ“ä½œã‚’ä¸å¿ƒã«èª¬æ˜Ž NumPy & SciPy ã‚’ä½¿ã£ãŸãƒ—ãƒã‚°ãƒ©ãƒŸãƒ³ã‚° â†’ ç·šå½¢å›žå¸°ã€ ä¸»æˆåˆ†åˆ†æž, K-Means â†’ Pythonã®ç‰¹å¾´ã§ã‚ã‚‹OOPã‚‚å–ã‚Šå…¥ã‚Œã‚‹ ndarrayã®viewã¨å‚ç…§æ¸¡ã— 4. WhatÂ isÂ NumPy/SciPy? Pythonã§æ•°å€¤è¨ˆç®— æ•°å€¤è¨ˆç®— â‰’ ç¹°ã‚Šè¿”ã—ä½œæ¥ã€ãƒ«ãƒ¼ãƒ— Pyhton : ãƒ«ãƒ¼ãƒ—ãŒé…ã„ã€ãã®ä»–è«¸ã€…ã¯æ›¸ãã‚„ã™ã„ã€‚ C,Fortran : ãƒ«ãƒ¼ãƒ—ãŒé€Ÿã„ã€å†—é•·ãªè¡¨ç¾ãŒå¤šã„
digimedaloter 2012/07/07
python

numpy
ãƒªãƒ³ã‚¯
1